dative {languageR} | R Documentation |
Data describing the realization of the dative as NP or PP in the Switchboard corpus and the Treebank Wall Street Journal collection.
data(dative)
A data frame with 3263 observations on the following 15 variables.
Speaker
Modality
spoken
, written
.Verb
SemanticClass
a
(abstract: 'give it some thought'),
c
(communication: 'tell, give me your name'),
f
(future transfer of possession: 'owe, promise'),
p
(prevention of possession: 'cost, deny'), and
t
(transfer of possession: 'give an armband, send').LengthOfRecipient
AnimacyOfRec
animate
and
inanimate
for the animacy of the recipient.DefinOfRec
definite
and
indefinite
coding the definiteness of the recipient.PronomOfRec
nonpronominal
and
pronominal
coding the pronominality of the recipient.LengthOfTheme
AnimacyOfTheme
animate
and
inanimate
coding the animacy of the theme.DefinOfTheme
definite
and
indefinite
coding the definiteness of the theme.PronomOfTheme
nonpronominal
and
pronominal
coding the pronominality of the theme.RealizationOfRecipient
NP
and
PP
coding the realization of the dative.AccessOfRec
accessible
,
given
, and new
coding the accessibility of the recipient.AccessOfTheme
accessible
,
given
, and new
coding the accessibility of the theme.Bresnan, J., Cueni, A., Nikitina, T. and Baayen, R. H. (2007) Predicting the dative alternation, in Bouma, G. and Kraemer, I. and Zwarts, J. (eds.), Cognitive Foundations of Interpretation, Royal Netherlands Academy of Sciences, 33 pages, in press.
## Not run: data(dative) # analysis with CART tree library(rpart) # ---- initial tree dative.rp = rpart(RealizationOfRecipient ~ ., data = dative[ ,-c(1, 3)]) # exclude the columns with subjects, verbs plot(dative.rp, compress = TRUE, branch = 1, margin = 0.1) text(dative.rp, use.n = TRUE, pretty = 0) # ---- pruning the initial tree plotcp(dative.rp) dative.rp1 = prune(dative.rp, cp = 0.041) plot(dative.rp1, compress = TRUE, branch = 1, margin = 0.1) text(dative.rp1, use.n = TRUE, pretty = 0) # analysis with logistic regression # ---- logistic regression with the Design package library(Design) dative.dd = datadist(dative) options(datadist = 'dative.dd') dative.lrm = lrm(RealizationOfRecipient ~ AccessOfTheme + AccessOfRec + LengthOfRecipient + AnimacyOfRec + AnimacyOfTheme + PronomOfTheme + DefinOfTheme + LengthOfTheme+ SemanticClass + Modality, data = dative) anova(dative.lrm) par(mfrow = c(4,3)) plot(dative.lrm) par(mfrow = c(1,1)) # ---- mixed-effects logistic regression with the lme4 package library(lme4) dative.lmer = lmer(RealizationOfRecipient ~ AccessOfTheme + AccessOfRec + LengthOfRecipient + AnimacyOfRec + AnimacyOfTheme + PronomOfTheme + DefinOfTheme + LengthOfTheme + SemanticClass + Modality + (1|Verb), data = dative, family = "binomial") print(dative.lmer, corr=FALSE) ## End(Not run)